About retrieval finetune question?

[Subury]

Can you share with the parameters setting during retrieval finetune? I try to use the define settings of code , but the results have very difference between the paper.

[SuperSupermoon]

@Subury Thanks for your interest. Could you please give me more detailed settings? As we described our paper and code, if you followed our code, the results should be the same. Therefore, I wonder your detailed settings. Then, we can catch the gap between us.

[Subury]

I think that the code on the "/MedViLL/downstream_task/retrieval/retrieval.py", which only has "Bidirectional" attention part. So, I use the "Bidrectional" pretrained weight to init finetune network, use the cmd of

"python retrieval.py --batch_size=18 --weight_load=True --load_pretrained_model=/MedViLL/pretrained/bi --epochs=50 --lr=1.8e-5"

to train.

In the inference phase, use the cmd of

"python retrieval.py --t2i=True --eval_len_size=1536 --do_train=False --do_test=True --label_conditioned_test_dataset=/dataset/MedViLL/T2I_Label_Test.jsonl --weight_load=True --load_pretrained_model=./output/2022-12-16\ 16:16:15.057888/49 --batch_size=160 --num_workers=8".

Thank you for your prompt reply.